def Registration(dir_res, fixed_image_path, moving_image_path, parameter_path, ELASTIX_PATH, pnr, anr, method, init):
"Function to registrate one moving on one fixed image. pnr should be given as 'p102'"
# Make a results folder if non exists (in Codes_def folder)
if init:
output = dir_res+'results_{}_{}/'.format(method, pnr)
output_dir = output+'atlas_{}'.format(anr)
if os.path.exists(output) is False:
os.mkdir(output)
if os.path.exists(output_dir) is False:
os.mkdir(output_dir)
else:
output = dir_res+'results_{}/'.format(pnr)
output_dir = output+'atlas_{}'.format(anr)
if os.path.exists(output) is False:
os.mkdir(output)
if os.path.exists(output_dir) is False:
os.mkdir(output_dir)
el = elastix.ElastixInterface(elastix_path=ELASTIX_PATH)
el.register(
fixed_image=fixed_image_path,
moving_image=moving_image_path,
parameters=[parameter_path],
output_dir=output_dir)
return output_dir
def get_el(ELASTIX_PATH):
if not os.path.exists(ELASTIX_PATH):
raise IOError(
'Elastix cannot be found, please set the correct ELASTIX_PATH.')
# Define a new elastix object 'el' with the correct path to elastix
el = elastix.ElastixInterface(elastix_path=ELASTIX_PATH)
return el
def Registration(fixed_image_path, atlas_path, ELASTIX_PATH, pnr):
"Function does registration for one atlas with one fixed image"
parameter_file_path = r'TrainingData\parameters.txt'
# Make a results directory if non exists
if os.path.exists('results_{}'.format(pnr)) is False:
os.mkdir('results_{}'.format(pnr))
el = elastix.ElastixInterface(elastix_path=ELASTIX_PATH)
el.register(fixed_image=fixed_image_path,
moving_image=atlas_path,
parameters=[parameter_file_path],
output_dir='results_{}'.format(pnr))
def Registration(fixed_image_path, atlas_path, parameter_path, ELASTIX_PATH,
pnr):
"Function to registrate one atlas on one fixed image. pnr should be given as 'p102'"
# Make a results directory if non exists
if os.path.exists('Results/results_{}'.format(pnr)) is False:
os.mkdir('Results/results_{}'.format(pnr))
el = elastix.ElastixInterface(elastix_path=ELASTIX_PATH)
output_dir = 'Results/results_{}'.format(pnr)
el.register(fixed_image=fixed_image_path,
moving_image=atlas_path,
parameters=[parameter_path],
output_dir=output_dir)
return output_dir
def registration(parameters, fix_im_p, mov_im_p, mov_im_m_p, name):
ELASTIX_PATH = os.path.join(
r'C:\Users\s148534\PycharmProjects\myfolder\elastix.exe')
TRANSFORMIX_PATH = os.path.join(
r'C:\Users\s148534\PycharmProjects\myfolder\transformix.exe')
if not os.path.exists(ELASTIX_PATH):
raise IOError(
'Elastix cannot be found, please set the correct ELASTIX_PATH.')
if not os.path.exists(TRANSFORMIX_PATH):
raise IOError(
'Transformix cannot be found, please set the correct TRANSFORMIX_PATH.'
)
# Define a new elastix object 'el' with the correct path to elastix
el = elastix.ElastixInterface(elastix_path=ELASTIX_PATH)
# Make a results directory if none exists
if not os.path.exists('results' + name):
os.mkdir('results' + name)
# # Execute the registration. Make sure the paths below are correct, and
# that the results folder exists from where you are running this script
parm = parameters
el.register(fixed_image=fix_im_p,
moving_image=mov_im_p,
parameters=[os.path.join(parm)],
output_dir='results' + name)
# Find the results
transform_path = os.path.join('results' + name,
'TransformParameters.0.txt')
tr_im_p = os.path.join('results' + name, 'result.0.mhd')
# Make a new transformix object tr with the CORRECT PATH to transformix
tr = elastix.TransformixInterface(parameters=transform_path,
transformix_path=TRANSFORMIX_PATH)
# Make a results directory if none exists
if not os.path.exists('results_tr' + name):
os.mkdir('results_tr' + name)
tr_im_m_p = tr.transform_image(mov_im_m_p, output_dir=r'results_tr' + name)
return tr_im_p, tr_im_m_p
def BSplineOnly(f, m, p, path, elastix_path, output, plot=False):
"Peforms BSpline transformation, using the fixed image, moving image, provided parameter file"
E = elastix.ElastixInterface(elastix_path)
E.register(fixed_image=f,
moving_image=m,
parameters=[p],
output_dir=output)
if plot == True:
for i in range(4):
L = elastix.logfile('{}\IterationInfo.0.R{}.txt'.format(path, i))
# Plot the 'metric' against the iteration number 'itnr'
plt.figure()
plt.plot(L['itnr'], L['metric'])
plt.tight_layout()
plt.xlabel('Iteration Number', size=16)
plt.ylabel('Mattes Mutual Information', size=16)
plt.xticks(size=14)
plt.yticks(size=14)
unseen_index = patients.index(unseen)
unseen_folder = 'results{}'.format(unseen)
# Make a results directory if non exists
if not os.path.exists(unseen_folder):
os.mkdir(unseen_folder)
# Get unseen mri and segmentations
unseen_image_path = os.path.join(unseen, 'mr_bffe.mhd')
image_array_unseen = sitk.GetArrayFromImage(sitk.ReadImage(unseen_image_path))
opr_image_path = os.path.join(unseen, 'prostaat.mhd')
image_array_opr = sitk.GetArrayFromImage(sitk.ReadImage(opr_image_path))
# Define a new elastix object 'el' with the correct path to elastix
el = elastix.ElastixInterface(elastix_path=ELASTIX_PATH)
DSC = []
SNS = []
SPC = []
finalMI = []
# Execute the registrations.
for i, patient in enumerate(patients):
# Reading patient segmentation and mri
pr_image_path = os.path.join(patient, 'prostaat.mhd')
mr_image_path = os.path.join(patient, 'mr_bffe.mhd')
# Everything for this registration will be put in result_path
pat_folder = 'result_unseen{}_{}'.format(unseen, patient)
def register_patients(fixed_subject, moving_subject, result_dir_start):
image_folder = "TrainingData"
param_file = 'Training/3Dtrans.txt'
param_file_spline = 'Training/3Dspline.txt'
result_dir = os.path.join(result_dir_start, "trans")
fixed_subject_path = os.path.join(image_folder, fixed_subject)
moving_subject_path = os.path.join(image_folder, moving_subject)
fixed_img_path = os.path.join(fixed_subject_path, 'mr_bffe.mhd')
fixed_seg_img_path = os.path.join(fixed_subject_path, 'prostaat.mhd')
moving_img_path = os.path.join(moving_subject_path, 'mr_bffe.mhd')
moving_seg_img_path = os.path.join(moving_subject_path, 'prostaat.mhd')
fixed_img = sitk.GetArrayFromImage(sitk.ReadImage(fixed_img_path))
fixed_seg_img = sitk.GetArrayFromImage(sitk.ReadImage(fixed_seg_img_path))
moving_img = sitk.GetArrayFromImage(sitk.ReadImage(moving_img_path))
moving_seg_img = sitk.GetArrayFromImage(
sitk.ReadImage(moving_seg_img_path))
# Define a new elastix object 'el' with the correct path to elastix
el = elastix.ElastixInterface(elastix_path=ELASTIX_PATH)
# Make a results directory if none exists
if not os.path.exists(result_dir):
os.mkdir(result_dir)
elif len(os.listdir(result_dir)) != 0:
inp = input("OK to overwrite? (y/n) ")
if inp != 'y':
sys.exit()
# Execute the registration. Make sure the paths below are correct, and
# that the results folder exists from where you are running this script
##pre-translation of the moving image
el.register(fixed_image=fixed_img_path,
moving_image=moving_img_path,
parameters=[param_file],
output_dir=result_dir)
# Find the results
transform_path = os.path.join(result_dir, 'TransformParameters.0.txt')
#result_path = os.path.join(result_dir, 'result.0.mhd')
'''
# Open the logfile into the dictionary log
for i in range(5):
log_path = os.path.join(result_dir, 'IterationInfo.0.R{}.txt'.format(i))
log = elastix.logfile(log_path)
# Plot the 'metric' against the iteration number 'itnr'
plt.plot(log['itnr'], log['metric'])
plt.legend(['Resolution {}'.format(i) for i in range(5)])
'''
#transformed_moving_image = sitk.GetArrayFromImage(sitk.ReadImage(os.path.join(result_dir,'result.0.mhd')))
# Make a new transformix object tr with the CORRECT PATH to transformix
tr = elastix.TransformixInterface(parameters=transform_path,
transformix_path=TRANSFORMIX_PATH)
# Transform a new image with the transformation parameters
img_out = os.path.join(result_dir, 'image')
if not os.path.exists(img_out):
os.mkdir(img_out)
seg_out = os.path.join(result_dir, 'segmentation')
if not os.path.exists(seg_out):
os.mkdir(seg_out)
t_img_path = tr.transform_image(moving_img_path, output_dir=img_out)
t_seg_path = tr.transform_image(moving_seg_img_path, output_dir=seg_out)
#t_img = sitk.GetArrayFromImage(sitk.ReadImage(t_img_path))
#t_seg_img = sitk.GetArrayFromImage(sitk.ReadImage(t_seg_path))
##B spline registration
result_dir = os.path.join(result_dir_start, 'Bspline')
if not os.path.exists(result_dir):
os.mkdir(result_dir)
el.register(fixed_image=fixed_img_path,
moving_image=t_img_path,
parameters=[param_file_spline],
output_dir=result_dir)
transform_path2 = os.path.join(result_dir, 'TransformParameters.0.txt')
#result_path2 = os.path.join(result_dir, 'result.0.mhd')
tr = elastix.TransformixInterface(parameters=transform_path2,
transformix_path=TRANSFORMIX_PATH)
# Transform a new image with the transformation parameters
img_out = os.path.join(result_dir, 'image')
if not os.path.exists(img_out):
os.mkdir(img_out)
seg_out = os.path.join(result_dir, 'segmentation')
if not os.path.exists(seg_out):
os.mkdir(seg_out)
t_img_path2 = tr.transform_image(t_img_path, output_dir=img_out)
t_seg_path2 = tr.transform_image(t_seg_path, output_dir=seg_out)
t_img2 = sitk.GetArrayFromImage(sitk.ReadImage(t_img_path2))
t_seg_img2 = sitk.GetArrayFromImage(sitk.ReadImage(t_seg_path2))
dice = dice_overlap(t_seg_img2, fixed_seg_img)
print('Dice similarity score with ground truth is {}'.format(dice))
#visualization of the results
visualize_patient(fixed_img, fixed_seg_img, moving_img, moving_seg_img,
t_img2, t_seg_img2)
'''
for i in range(np.shape(t_seg_img2)[0]):
fig, ax = plt.subplots(1, 3, figsize=(10, 15))
ax[0].imshow(moving_seg_img[i,:,:], cmap='gray')
ax[0].set_title('Ground Truth')
ax[1].imshow(t_seg_img2[i,:,:], cmap='gray')
ax[1].set_title('Estimation')
ax[2].imshow(fixed_seg_img[i,:,:], cmap='gray')
ax[2].set_title('Fixed Atlas')
plt.show()
#make video of images
out = cv2.VideoWriter('project.avi',cv2.VideoWriter_fourcc('M','J','P','G'), float(10), (np.shape(t_img2)[2],np.shape(t_img2)[1]), isColor=True)
for i in range(np.shape(t_seg_img2)[0]):
out.write(t_seg_img2[i,:,:])
out.release()
'''
#
## Get the Jacobian matrix
#jacobian_matrix_path = tr.jacobian_matrix(output_dir=result_dir)
#
## Get the Jacobian determinant
#jacobian_determinant_path = tr.jacobian_determinant(output_dir=result_dir)
#
## Get the full deformation field
#deformation_field_path = tr.deformation_field(output_dir=result_dir)
#
#jacobian_image = imageio.imread(jacobian_determinant_path.replace('dcm', 'tiff'))
#jacobian_binary = jacobian_image>0
#
## Add a plot of the Jacobian determinant (in this case, the file is a tiff file)
#ax[3].imshow(jacobian_binary,cmap='gray')
#ax[3].set_title('Jacobian\ndeterminant')
return t_seg_img2, dice
#visualisation commands
#visualize2d(fixednr,movingnr,slicenr,runnr)
#visualize3d(fixednr,movingnr,slicenr,runnr)
fixedmask = findfixedmask(107)
transformedmask = findtransformedmask(runnr)
print(medpyDC(transformedmask, fixedmask))
print(medpyHD(transformedmask, fixedmask))
fixed_image_path = os.path.join(f"results{runnr}", "result.mhd")
moving_image_path = os.path.join(data_path, f"p{movingnr}\mr_bffe.mhd")
output_dir = f'results{runnr}'
el = elastix.ElastixInterface(elastix_path=elastix_path)
#run model
el.register(fixed_image=fixed_image_path,
moving_image=moving_image_path,
parameters=[parameter_file2],
output_dir=output_dir)
transformedmask2 = findtransformedmask(runnr)
print(medpyDC(transformedmask, fixedmask))
print(medpyHD(transformedmask, fixedmask))
print(medpyDC(transformedmask2, fixedmask))
print(medpyHD(transformedmask2, fixedmask))
#
#im1 = r'C:\Users\s081992\Documents\TUE\Year 2\Q3\Capita Selecta\Part 2\PracticalSession2019 2\PracticalSession2019\chest_xrays\moving_image.mhd'
#im2 = r'C:\Users\s081992\Documents\TUE\Year 2\Q3\Capita Selecta\Part 2\PracticalSession2019 2\PracticalSession2019\chest_xrays\fixed_image.mhd'
im1 = 'C:\\Users\\s081992\\Documents\\TUE\\Year 2\\Q3\\Capita Selecta\\Part 2\\TrainingData\\TrainingData\\p102\\mr_bffe.mhd'
im2 = 'C:\\Users\\s081992\\Documents\\TUE\\Year 2\\Q3\\Capita Selecta\\Part 2\\TrainingData\\TrainingData\\p107\\mr_bffe.mhd'
#im1 = 'C:\\Users\\s081992\\Documents\\TUE\\Year 2\\Q3\\Capita Selecta\\Part 2\\TrainingData\\TrainingData\\p102\\prostaat.mhd'
#im2 = 'C:\\Users\\s081992\\Documents\\TUE\\Year 2\\Q3\\Capita Selecta\\Part 2\\TrainingData\\TrainingData\\p107\\prostaat.mhd'
#im1raw = r'C:\Users\s081992\Documents\TUE\Year 2\Q3\Capita Selecta\Part 2\PracticalSession2019 2\PracticalSession2019\chest_xrays\moving_image.raw'
#im2raw = r'C:\Users\s081992\Documents\TUE\Year 2\Q3\Capita Selecta\Part 2\PracticalSession2019 2\PracticalSession2019\chest_xrays\fixed_image.raw'
# Define a new elastix object 'E' with the CORRECT PATH to elastix
E = elastix.ElastixInterface(
elastix_path=
r'C:\Users\s081992\Documents\TUE\Year 2\Q3\Capita Selecta\Part 2\PracticalSession2019 2\PracticalSession2019\Software\Software\elastix_windows64_v4.7\elastix.exe'
)
# Execute the registration. Make sure the paths below are correct, and
# that the results folder exists from where you are running this script
#%%
#path = r'C:\Users\s081992\Documents\TUE\Year 2\Q3\Capita Selecta\Part 2\TrainingData\TrainingData\p102\mr_bffe.mhd'
#image = sitk.ReadImage(path)
#as_array = sitk.GetArrayFromImage(image)
#
#
#
#import SimpleITK as sitk
#image = sitk.ReadImage(im1raw)